Mariano Carbonero-Ruz

26 papers C 1Misc 1Journal 15Unranked 7
YearRankTypeTitle / Venue / Authors
2025 J jnl
Enhancing financial time series forecasting through topological data analysis.
Neural Comput. Appl.
Luiz Carlos de Jesus Jr., Francisco Fernández-Navarro, Mariano Carbonero-Ruz
2023 J jnl
A multi-class classification model with parametrized target outputs for randomized-based feedforward neural networks.
Appl. Soft Comput.
Antonio Manuel Durán-Rosal, Aggeo Durán-Fernández, Francisco Fernández-Navarro, Mariano Carbonero-Ruz
2022 J jnl
Global Negative Correlation Learning: A Unified Framework for Global Optimization of Ensemble Models.
IEEE Trans. Neural Networks Learn. Syst.
Carlos Perales-González, Francisco Fernández-Navarro, Mariano Carbonero-Ruz, Javier Pérez-Rodríguez
2021 J jnl
An experimental study on diversification in portfolio optimization.
Expert Syst. Appl.
Luisa Martínez-Nieto, Francisco Fernández-Navarro, Mariano Carbonero-Ruz, Teresa Montero-Romero
2021 J jnl
Negative Correlation Hidden Layer for the Extreme Learning Machine.
Appl. Soft Comput.
Carlos Perales-González, Francisco Fernández-Navarro, Javier Pérez-Rodríguez, Mariano Carbonero-Ruz
2020 J jnl
Negative correlation learning in the extreme learning machine framework.
Neural Comput. Appl.
Carlos Perales-González, Mariano Carbonero-Ruz, Javier Pérez-Rodríguez, David Becerra-Alonso, Francisco Fernández-Navarro
2019 J jnl
Multi-objective evolutionary optimization using the relationship between F 1 and accuracy metrics in classification tasks.
Appl. Intell.
Juan Carlos Fernández, Mariano Carbonero-Ruz, Pedro Antonio Gutiérrez, César Hervás-Martínez
2019 J jnl
Regularized ensemble neural networks models in the Extreme Learning Machine framework.
Neurocomputing
Carlos Perales-González, Mariano Carbonero-Ruz, David Becerra-Alonso, Javier Pérez-Rodríguez, Francisco Fernández-Navarro
2018 Misc conf
A Preliminary Study of Diversity in Extreme Learning Machines Ensembles.
HAIS
Carlos Perales-González, Mariano Carbonero-Ruz, David Becerra-Alonso, Francisco Fernández-Navarro
2017 J jnl
A two dimensional accuracy-based measure for classification performance.
Inf. Sci.
Mariano Carbonero-Ruz, Francisco J. Martínez-Estudillo, Francisco Fernández-Navarro, David Becerra-Alonso, Alfonso C. Martínez-Estudillo
2017 J jnl
Global Sensitivity Estimates for Neural Network Classifiers.
IEEE Trans. Neural Networks Learn. Syst.
Francisco Fernández-Navarro, Mariano Carbonero-Ruz, David Becerra-Alonso, Mercedes Torres-Jiménez
2016 — conf
Adapting linear discriminant analysis to the paradigm of learning from label proportions.
SSCI
María Pérez-Ortiz, Pedro Antonio Gutiérrez, Mariano Carbonero-Ruz, César Hervás-Martínez
2016 — conf
Learning from Label Proportions via an Iterative Weighting Scheme and Discriminant Analysis.
CAEPIA
María Pérez-Ortiz, Pedro Antonio Gutiérrez, Mariano Carbonero-Ruz, César Hervás-Martínez
2016 J jnl
Semi-supervised learning for ordinal Kernel Discriminant Analysis.
Neural Networks
M. Pérez-Ortiz, Pedro Antonio Gutiérrez, Mariano Carbonero-Ruz, César Hervás-Martínez
2012 J jnl
A two-stage evolutionary algorithm based on sensitivity and accuracy for multi-class problems.
Inf. Sci.
Pedro Antonio Gutiérrez, César Hervás-Martínez, Francisco J. Martínez-Estudillo, Mariano Carbonero-Ruz
2012 — conf
Evolutionary Extreme Learning Machine for Ordinal Regression.
ICONIP (3)
David Becerra-Alonso, Mariano Carbonero-Ruz, Francisco J. Martínez-Estudillo, Alfonso C. Martínez-Estudillo
2011 — conf
A Hybrid Evolutionary Approach to Obtain Better Quality Classifiers.
IWANN (2)
David Becerra-Alonso, Mariano Carbonero-Ruz, Francisco J. Martínez-Estudillo, Alfonso C. Martínez-Estudillo
2011 J jnl
Evolutionary q-Gaussian radial basis function neural networks for multiclassification.
Neural Networks
Francisco Fernández-Navarro, César Hervás-Martínez, Pedro Antonio Gutiérrez, Mariano Carbonero-Ruz
2011 C conf
Numerical variable reconstruction from ordinal categories based on probability distributions.
ISDA
Javier Sánchez-Monedero, Mariano Carbonero-Ruz, David Becerra-Alonso, Francisco J. Martínez-Estudillo, Pedro Antonio Gutiérrez, César Hervás-Martínez
2010 — conf
Evolutionary
HAIS (2)
Francisco Fernández-Navarro, César Hervás-Martínez, Pedro Antonio Gutiérrez, Manuel Cruz-Ramírez, Mariano Carbonero-Ruz
2010 — conf
Evolutionary Learning Using a Sensitivity-Accuracy Approach for Classification.
HAIS (2)
Javier Sánchez-Monedero, César Hervás-Martínez, Francisco J. Martínez-Estudillo, Mariano Carbonero-Ruz, M. C. Ramírez Moreno, Manuel Cruz-Ramírez
2009 J jnl
Combined projection and kernel basis functions for classification in evolutionary neural networks.
Neurocomputing
Pedro Antonio Gutiérrez, César Hervás, Mariano Carbonero-Ruz, Juan Carlos Fernández
2009 — ch.
Multilogistic Regression by Product Units.
Encyclopedia of Artificial Intelligence
Pedro Antonio Gutiérrez, César Hervás, Francisco J. Martínez-Estudillo, Mariano Carbonero-Ruz
2008 — ch.
Combined Projection and Kernel Basis Functions for Classification in Evolutionary Neural Networks.
Innovations in Hybrid Intelligent Systems
Pedro Antonio Gutiérrez, César Hervás-Martínez, Mariano Carbonero-Ruz, Juan Carlos Fernández
2008 J jnl
Multilogistic regression by means of evolutionary product-unit neural networks.
Neural Networks
César Hervás-Martínez, Francisco J. Martínez-Estudillo, Mariano Carbonero-Ruz
2007 — conf
Evolutionary Combining of Basis Function Neural Networks for Classification.
IWINAC (1)
César Hervás, Francisco José Martínez, Mariano Carbonero-Ruz, Cristóbal Romero, Juan Carlos Fernández